A network-based analysis detects cocaine-induced changes in social interactions in Drosophila melanogaster

Addiction is a multifactorial biological and behavioral disorder that is studied using animal models, based on simple behavioral responses in isolated individuals. A couple of decades ago it was shown that Drosophila melanogaster can serve as a model organism for behaviors related to alcohol, nicotine and cocaine (COC) addiction. Scoring of COC-induced behaviors in a large group of flies has been technologically challenging, so we have applied a local, middle and global level of network-based analyses to study social interaction networks (SINs) among a group of 30 untreated males compared to those that have been orally administered with 0.50 mg/mL of COC for 24 hours. In this study, we have confirmed the previously described increase in locomotion upon COC feeding. We have isolated new network-based measures associated with COC, and influenced by group on the individual behavior. COC fed flies showed a longer duration of interactions on the local level, and formed larger, more densely populated and compact, communities at the middle level. Untreated flies have a higher number of interactions with other flies in a group at the local level, and at the middle level, these interactions led to the formation of separated communities. Although the network density at the global level is higher in COC fed flies, at the middle level the modularity is higher in untreated flies. One COC specific behavior that we have isolated was an increase in the proportion of individuals that do not interact with the rest of the group, considered as the individual difference in COC induced behavior and/or consequence of group influence on individual behavior. Our approach can be expanded on different classes of drugs with the same acute response as COC to determine drug specific network-based measures and could serve as a tool to determinate genetic and environmental factors that influence both drug addiction and social interaction.

Our response. Thank you very much for this comment. We inadvertently neglected to include all the information in the first version of the manuscript. Now we have provide all the necessary information about the origin of the cocaine used in our study.
3. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, all author-generated code must be made available without restrictions upon publication of the work.
Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse.
Our response. We shared all our tracking data and code package freely online under BSD-3 License, so it can be further used.
Reviewer #1: 1. The article by Petrovic et al. describes a novel analysis package, NetworkX, to analyze interactions amongst 30 male flies, as captured by video tracking. Authors extract a (large) number of measured parameters, some of which change in flies that have been fed cocaine for a day. I am unconvinced of the authors interpretations as to the meaning of the data, and the data differences. These (overinterpreted) statements thus should go into the discussion, and not the results and methods. Other than that, the paper is solid, requires some textual edits, and will thusly be in good shape.
Our response. We thank the reviewer for useful comments and suggestions how to improve our manuscript. We rewrote all unclear parts of the manuscript and moved statements related to interpretation to the Discussion section. We agree that certain parts of the manuscript were over interpreted, we have completely removed these statements and "toned down" some of our conclusions.

Major interpretative issues:
2. Exposure to cocaine does not "validate" the findings on the myriad of parameters with NetworkX, since it is NOT clear -a priori -what the expected outcomes should be. It was maybe a missed opportunity to actually validate the software with mutants that have been described before in the triangle social interaction assay, e.g. Nlg3. Or say some setups with predictable interactions, all males, vs 15 males with 15 virgins. In the absence of that, the software may very well extract reproducible data (but see Fig5B), but what those data actually mean, is a different (and unanswered) question.
Our response. This is very important remark, thank you. We now realise that in the first version of our manuscript we did not clearly explain the validation of the proposed approach (and software). We rewrote certain parts of the manuscript in order to explain the validation procedure.
We validate the proposed approach (software/methodology) by comparing network-based measures of COC and CTRL populations on the global network level.
Since it has already been confirmed by the previous experiments that there are differences in locomotor activities and behaviour of cocaine-induced D. Melanogaster (McClung C, Hirsh J. Stereotypic behavioral responses to free-base cocaine and the development of behavioral sensitization in Drosophila. Current Biology. 1998;8(2):109-112, Filošević A, Al-samarai S, Andretic R. High Throughput Measurement of Locomotor Sensitization to Volatilized Cocaine in Drosophila melanogaster. Frontiers in Molecular Neuroscience. 2018;11:25), we expected that networks of COC would exhibit different properties from the CTRL networks, especially in values of the network measures based on a number of interaction and distance. Therefore, we compared 13 network measures on the global level and confirmed expected differences between COC and CTRL populations. Encouraged by these findings, in the next step we used local and middle network measures to identify changes in SINs of COC populations.
We agree that validation performed by using mutants is an important procedure and we plan to do that in future work. However, we believe that the influence of cocaine on the olfactory sensors is insufficiently investigated.
Additionally, we use only male flies for study of addiction so we did not optimized our method to be influenced by females, but in the future work we will focused on different social background to define its influence on social behaviour of individuals in the group.
2. Therefore, some of the writing needs to be toned down, specifically: "[abstract] Larger and denser communities of COC treated flies can be explained by heighten arousal and repetitive behaviors." Heightened arousal maybe, but I can't recall repetitive social stereotypies being described in the Drosophila cocaine exposure literature. Sounds like conjecture that can go into the discussion, but not into the abstract.
" [abstract] Our work showed that social network analysis using NetworkX identifies biologically relevant parameters that can be used…" Relevant for what? Is the definition of relevant here: to be measurable and affected by cocaine?
"l.277 because information in this context is an inverse to the path length" to a social behavioral biologist information has little to do with path length. "l.291 indicating that nodes had no influence on the flow of information in the network" what is the definition of "flow of information" here? "l.345 Ultimately, this leads to higher global efficiency in the COC relative to CTRL networks." What does efficiency mean here?
Our response. Thank you for these remarks, we agree with all your suggestions. We rewrote the abstract and tried to clarify the motivation of this research. We moved texts related to the interpretation to the Discussion section. We toned down our interpretations and tried to explain concepts from complex network theory, such as path length and global efficiency. Regarding global efficiency and information flow we agree that these interpretations and conclusions go too far and therefore we provide a discussion without over interpretation.
3. Second: the paper needs to be a bit more accessible to general readers. The problem is that the manuscript marries two distant fields: engineering/data science with behavioral biology. Each of these fields has its own jargon, or even definition of certain words: "information flow" in a system does not have the same implications as "information flow" between sentient beings. Thus authors need to keep naïve readers from EITHER discipline in mind, and they also need to precisely define what they mean with certain key terms.
Our response. Thank you for this suggestion. Now we rewrote the methodology section (and all other critical parts of our manuscript) aiming to better explain all technical terms. Therefore, we provide a more detailed explanation of network-based measures -using terminology related to the D. melanogaster domain -flies (represented using nodes) and interactions (represented using links). 4. Third: It's a bit odd to see all these t-tests (in the supplement), when the data is displayed with medians and quartiles. Seems to require non-parametric testing and some adjusting of the p-value (with so many comparisons). Also, why paired tests (given there were 9 ctl, but 11 coc experiments)?
Our response. We corrected that. We now performed statistical analysis using independent-samples t-tests. These tests are Welch-corrected since group sizes are different and variance should thus not be assumed equal and significance level of p < 0.05. We explained that in the paper and correct results in the supplement.
Minor: 5. Abstract: "Importantly the differences were complementary within each level of analysis and consistent among different levels." not sure this is well explained in the text.
Our response. Thank you for this remark. We reformulated this sentence and explained better what we wanted to say. 6. Fig1D legend: is standing away 4mm from another fly really an interaction? Why 4mm, why not 3 or 5, or 0, really? Was this parameter explored and determined heuristically, or is this based on some assumption, or some relevant published data? And where do these 4mm start/end? At the centroid? At the periphery facing the interactor (as suggested by the figure). Then again, in the methods it says "focused on touch". Confusing! Our response. That is a good question. We explained that in more detail in the new version of our manuscript. The criteria of how many body lengths and what time should be considered as social interaction are taken from the similar experiment setup published in the related study that quantified these values (Schneider et al, 2014). 7. Is a node a fly? The same fly followed over 10 min? a snapshot in time? (actually, nodes represent the flies, not the other way around l.115).
Our response. Yes, flies are represented using nodes. One node represents the same fly followed in the snapshot time. We tried to clarify that in the new version of our manuscript. 8. l.119: "For each network we introduced two variants of weight factors:.." is this supposed to mean: for each interaction we measured two variables…represented in the network as… the rest is also confusing. What if two flies make contact in minute 2, and again in minute 8. How is that represented? Same link? Thus l.121 should read "number of times the same flies made contact during the 10-min observation period…"? Our response. Thank you for that comment. We are aware that in our first submission we did not clearly explain weights. We thank the reviewer for pointing this out. We rewrote this paragraph and tried to clarify how we construct a weighted network. If two flies, make contact in minute 2, and again in minute 8 it is represented using the same link. In one case, the weight would be 10 (which is the total duration of files interaction) and in the second case, the weight would be 2, because there were two interactions between these two flies. 9. L126: "In following subsections we provide definitions and interpretations of the.." Definitions, yes; interpretations: no. Interpretations go into the discussion, since I see no evidence provided that centrality equates to "the most influential individuals". That's too much anthropomorphizing! Same with "which nodes control the network (in terms of information flow)". There is no evidence a specific fly is socially 'dominant' in controlling information flow. I posit that if you take 30 marbles and gently shake them, the analysis will find some marbles that are more dominant, just by chance. Considerably more work is required to infer any meaning into the data as authors are doing, the easiest of which would have been to ask how reproducible are these networks are in a 30 min movie of the same flies analyzed as 3x10 min. IS there really a reproducibly popular, or 'dominant' node? ARE there reproducible assortative groups?
Our response. We thank the reviewer for the suggestions regarding the interpretation of SINs measures. We agree that there is no evidence for our interpretations claimed in these subsections. We rewrote parts of the section "Characterisation of SINs" and removed all attempts to interpret the network measures. This way, some of the interpretations are deleted and some are moved to the Discussion section.
10. Fig. 3A: the median is lower in coc, but the quartiles are higher. How can that really be interpreted meaningfully? Also, it says "average" in the legend, which normally means "mean", but such details are not explained cogently. And how do you pair these samples!?! Each dot is a node=fly, and each ctl fly has a sibling fly in the coc group??? That makes no sense… Our response. Fig. 3 (in the new version it is Fig. 4) illustrates differences between CTRL and COC SINs in three local network measures: degree centrality, closeness centrality and clustering coefficient. In this figure each dot is a node=fly, however, there are no "siblings" because we do not have paired samples of SINs. We compared values of local network measures of flies from both populations illustrating separately COC population and CTRL population.
As you said, in Fig. 3A (Now it is Fig, 4A): the median is lower in COC populations, but the quartiles are higher. This can be explained by the fact that there are 20% of isolated flies (with no interactions) in COC networks are outliers and do not belong to any quartile. At the same time, these flies are taken into account when calculating the median.. 11. Fig4B gives one pause regarding reproducibility, especially the ctl side.
Our response. This is a good question. Here we really have an outlier in the CTRL population with higher values of information centrality measure. It may seem that this would be a problem for reproducibility. Some similar studies treat these situations in the way that they remove outliers from the population. We decided to keep this outlier in order to show that in some groups of flies it is possible to have different behaviour. Since the other eight groups in the CTRL populations have similar values of network measures, we concluded that in general SINs of the CTRL population have lover values of information centrality. 11. l.289: "signifying that nodes have no influence on the network" huh? The network consists of linked nodes, how can they NOT have an effect? Unclear Our response. Thank you for noticing this mistake. We rewrote that paragraph and deleted this mistake.
12. l.290: "SINs does not influence flies thought the incoming links" that's not English, but also, why are we talking about flies now, not nodes?
Our response. We rewrote that paragraph and removed all the unclear parts of the text.

Reviewer #2:
This article is the validation of a new technique to quantify Social Interaction Networks (SIN) in flies, assessing the effect of feeding cocaine to the flies on emerging properties of SINs, in a group of 30 males, which had never been done before.
It is well written and easy to follow. The methodology is mostly clearly described (see comment below). The figures are well done, especially Fig1. The statistical analysis appears fair to me, the software used to analyze the video is made freely available. I particularly appreciated the fact that the authors describe very clearly the emerging properties, at 3 different levels (local, middle and global), and their interpretations. Our response. We appreciate this suggestion. We have included this study in our manuscript and compared it with our approach.
2. Methodology: well described, apart for the rationale behind the cocaine feeding section. Why feeding only 24 hours? Why 0.5 mg/ml? Ref?
Our response. Thank you for this remark. We somehow failed to write all these details, but we agree that this is important. We added all details about cocaine feeding. To ensure the complete reproducibility of our experiment, we have deposited the entire procedure and experimental setup at protocols.io. Reason for using 0.50 mg/mL of cocaine-HCl was based on previous work in our laboratory and other related published results . Since cocaine half-life is about 1.5 hours and flies were not starved priori of COC feeding, we want to ensure that concentration used in experiment won't be aversive to the flies since cocaine is bitter tasting substance. To be sure, that all flies have consumed COC we left them for 24 hours on food with COC and that does only increase locomotor activity and not induce other stereotypic behaviour associated with high doses (Rigo F, Filošević A, Petrović M, Jović K, Andretić Waldowski R. Locomotor sensitization modulates voluntary self-administration of methamphetamine in Drosophila melanogaster. Addiction Biology. 2021;26(3):e12963.) 3.Discussion: Overall, discussed different aspects and interpretation of the results presented. I have just one concern here. The authors discuss how sensory modalities, known to be important for SINs properties are received by FruP1 neurons, which in turn promote aggression or courtship. They also explain that the differences in the emerging properties of the flies fed cocaine versus control could be the result of increased arousal, similar to feeding methamphetamine. Also ppk is discussed. However, a whole section on the molecular targets of cocaine (DAT, VMAT), and how behaviours are known to be affect in flies after administering cocaine, or when the encoding genes are mutants is missing. Indeed, not only social behaviours are affected, but also locomotion, grooming etc… Those could also interfere with SINs, not only repetitive behavioural loops.
Our response. Thank you for this remark. We have add section about influence of cocaine on the dopamine transporters on presynaptic neurons and inside of neurons on vesicular monoamine transporter. We discussed influence of those protein targets on locomotor behaviour and sensitivity to acute dose of cocaine using Drosophila model. We also cited recent rodent study which shows that social interactions changes the activity of specific dopaminergic circuits that control drug craving, suggesting that social interaction has reinforcing influence on addictive behaviours.
Minor issues: 4. The raw data have not been available -only the software Our response. Thank you for this remark. We made all our data and softer available for further research.